MétaCan
Menu
← Back to cohort
Record W6989387469

Assumption of Responsibility and Loss of Bargain in\nTort Law

2006· article· en· W6989387469 on OpenAlexaff

Bibliographic record

VenueeYLS (Yale Law School) · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLaw, Economics, and Judicial Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTortDoctrineDamagesPrivity of contractProduct (mathematics)Dual (grammatical number)Common lawJob loss
DOInot available

Abstract

fetched live from OpenAlex

The author seeks to justify recovery in negligence law for loss of bargain, which is the pure economic loss incurred by a subsequent purchaser of a defective product or building structure in seeking to repair the defect. The difficulty is that the purchaser is not in a relationship of contractual privity with the manufacturer The conflicting approaches in Anglo-American tort law reveal confusion, owing to loss of bargain's dual implication of the law governing pure economic loss and products liability. These difficulties are overcome by drawing from Hedley Byrne's requirements of a defendant's assumption of responsibility and a plaintiff's reasonable reliance, and by casting the damaged interest as that of the plaintiff's own autonomy. In doing so, the doctrine of assumption of responsibility is encapsulated, and the case for its extension to loss of bargain cases is made with reference to early U.S. products liabilityjurisprudence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0040.023
Scholarly communication0.0070.009
Open science0.0020.006
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.223
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueeYLS (Yale Law School)→Same topicLaw, Economics, and Judicial Systems→French-language works237,207→